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Mathematical Problems in Engineering
Volume 2018 (2018), Article ID 2560153, 9 pages
Research Article

A Marketing Strategy in a Closed-Loop Supply Chain with Loss-Averse Consumers

1School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Jiangsu, China
2School of Mathematics and Information Science, Yantai University, Yantai, China

Correspondence should be addressed to Bi-feng Liao; moc.361@1101oailty

Received 10 May 2017; Accepted 7 November 2017; Published 10 January 2018

Academic Editor: Ibrahim Zeid

Copyright © 2018 Bi-feng Liao and Bang-yi Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The importance of remanufacturing system has been extensively investigated in recent years. Taking into account the consumer valuation uncertainty and the demand uncertainty, this paper addresses the issue of closed-loop supply chain with remanufacturing by game theory. We consider two types of consumers in the market: loss-neutral consumers and loss-averse consumers. The loss-neutral consumers are completely rational. The loss-averse consumers, on the other hand, are with losses being more painful than equal-sized gains being pleasant. When multichannel structure can be chosen, the manufacturer has three pricing strategies in direct market: keeping the price high with a small discount, no customers choose the online store; keeping the price high with a moderate discount, only the loss-neutral customers choose the online store; keeping the price low with a big discount, all customers choose the online store. Consumers make up their decisive selections through comparing the price and channel attributes. We introduce utility function for analyzing the market demand and then identify the optimal pricing and channel strategy to maximize the manufacturer’s profit. Finally, the rationality and validities of the proposed model are illustrated by numerical examples, and sensitivity analyses of the parameters are also presented.